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Overcoming the disadvantages of low transmission and broad peak bandwidth of previously reported plasmonic color filters, a high-efficiency multispectral plasmonic color filter is theoretically proposed with two cascaded ultrathin metallic nanogratings separated by two heterogeneous dielectric layers, and its optical properties are theoretically investigated using the finite-difference time-domain method. The transmission spectrum presents three near-unity peak bands accompanied with three near-null dip bands adjacent around them. Both transmission efficiencies of above 90% and ultranarrow peak bandwidth of 20 nm are achieved in the visible regime. The peak band positions can be flexibly tailored by varying the structural parameters. The filter selects the visible color with high signal noise ratio at the peak bands. The outstanding spectral properties of this filter indicate significant improvement for the high-accuracy color filtering and multispectral imaging applications. The simulated near-field electromagnetic distributions suggest that the excitation of the hybrid antisymmetric surface plasmon polariton (SPP) leaky mode and metal-insulator-metal waveguide modes are responsible for the peak transmission bands, while the formation of the hybrid SPP bound modes confined on the bottom nanograting makes the dip transmission bands, all of which are the consequence of the plasmonic hybridization between the two neighboring metallic nanogratings.

Abstract Tungsten trioxide (WO3) nanostructures were synthesized by hydrothermal method using sodium tungstate (Na2WO4·2H2O) alone as starting material, and sodium tungstate in presence of ferrous ammonium sulfate [(NH4)2Fe(SO4)2·6H2O] or cobalt chloride (CoCl2·6H2O) as structure-directing agents. Orthorhombic WO3having a rectangular slab-like morphology was obtained when Na2WO4·2H2O was used alone. When ferrous ammonium sulfate and cobalt chloride were added to sodium tungstate, hexagonal WO3nanowire clusters and hexagonal WO3nanorods were obtained, respectively. The crystal structure and orientation of the synthesized products were studied by X-ray diffraction (XRD), micro-Raman spectroscopy, and high-resolution transmission electron microscopy (HRTEM), and their chemical composition was analyzed by X-ray photoelectron spectroscopy (XPS). The optical properties of the synthesized products were verified by UV–Vis and photoluminescence studies. A photodegradation study on Procion Red MX 5B was also carried out, showing that the hexagonal WO3nanowire clusters had the highest photodegradation efficiency.

Deep learning solutions in big data applications can benefit cloud centres and can also lead to network communication overhead. Typically, data collected from traffic are sent to the traffic management centre for analysis. However, this process can worsen the network route to the traffic management centre. A two-tier mechanism has been developed to address this issue, which performs vehicle speed estimation and traffic congestion detection for efficient traffic management. The real-time traffic video data are captured and the video frames are initially processed through a foreground extraction process, which extracts the temporarily stopped vehicles on the road by removing background pixels from the frames. The video frames are then wrapped in an up-down view to remove the influence of the observation angle. The traffic congestion is then detected accurately based on the traffic characteristics using the proposed Ensemble Random Forest-based Gradient Optimization (ERF-GO) algorithm. The generalization error occurs when learning complex features on frames is minimized using a gradient-based optimization (GO) algorithm. Finally, the learned information on traffic conditions is forwarded to the cloud and edge computing environments based on network connection speed. The efficiency of the proposed ERF-GO is investigated in terms of performance metrics, namely root mean square error, speed detection error, execution time, computational cost, accuracy, latency, workload balance, precision, recall, f-measure, and congestion detection error rate. The analytic result displays that the proposed ERF-GO algorithm attains a greater accuracy rate of about 98.65% in detecting traffic congestion which is comparably higher than state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper presents the effect of the local low-pressure region in the atmosphere and rain on aerodynamic characteristics of medium altitude long endurance unmanned aerial vehicle (MALE-UAV) configuration during cruise/loiter. Computations are performed using CFD++, a commercial CFD software suite. A large low-pressure depression past the MALE UAV (symmetrically and asymmetrically) with pressure 10 - 15 % lower than the free stream pressure and a widespread rainfall type with a rainfall rate of 1195 mm/hr., are considered for CFD simulation. A large low pressure that spans the whole MALE-UAV results in a decrement in both lift and drag, but does not affect the yawing and rolling moments significantly. However, a low-pressure region that engulfs only one-half of MALE UAV causes sudden/abrupt changes in rolling and yawing moments. The effect of rain causes a significant decrease in a lift at higher alpha, accompanied by a decrease in stall angle of 2 degrees, and a significant increase in drag. From the study, a Standard Operating Procedure (SOP) was adopted to fly UAVs in adverse weather effects, such that the aircraft can be operated with a velocity higher than 1.3Vstall and at a power setting not less than 75% of max power capacity. [ABSTRACT FROM AUTHOR]